Sweet Spot: Glucose Control in the Intensive Care Unit.

Hyperglycemia, hypoglycemia, and glycemic variability are all independently associated with morbidity and mortality of critically ill patients. A strategy aiming at normoglycemia (so-called tight glycemic control) could improve outcomes of critically ill patients, but results from randomized controlled trials of tight glycemic control are conflicting. Strict glycemic control is associated with an increased risk of hypoglycemia, which could offset the benefit of this intervention. Notably, the risk of hypoglycemia is not necessarily removed with less tight glucose control regimens. The best targets of blood glucose control in critically ill patients, therefore, remain a matter of debate. It should be realized that blood glucose control is a complex intervention, consisting of many critical aspects that have the potential to affect its efficacy and safety. Efficacy, and in particular safety, of blood glucose control could still improve. First, glucose algorithms could overcome the lack of knowledge and skills of nursing staff when they are less experienced in safe and efficient blood glucose control. Several computerized glucose control algorithms have been developed over recent years, but they all need clinical validation. Also, the workload induced by such algorithms should be evaluated. Second, continuous blood glucose monitoring has the potential to improve safety and efficacy. Until recently, blood glucose levels were monitored manually using point-of-care devices with significant inaccuracies. Various continuous monitoring systems have been developed, but studies testing their accuracies and usefulness in an intensive care unit setting are highly needed.

Associations between bolus infusion of hydrocortisone, glycemic variability and insulin infusion rate variability in critically Ill patients under moderate glycemic control.

BACKGROUND: We retrospectively studied associations between bolus infusion of hydrocortisone and variability of the blood glucose level and changes in insulin rates in intensive care unit (ICU) patients. METHODS: 'Glycemic variability' and 'insulin infusion rate variability' were calculated from and expressed as the standard deviation (SD) of all blood glucose levels and insulin infusion rates during stay in the ICU, respectively. Glycemic and insulin infusion rate variability in patients who received bolus infusion of hydrocortisone were compared to those in patients who never received bolus infusion of hydrocortisone. Multivariate analysis was performed to correct for potential covariates including disease severity. RESULTS: We included 6409 patients over 6 years; of them 962 received bolus infusion of hydrocortisone. Compared to patients who never received bolus infusion of hydrocortisone, patients who received hydrocortisone had their blood glucose level measured more frequently, had higher glycemic variability; were more frequently treated with intravenous insulin and had higher insulin infusion rate variability. The association between hydrocortisone treatment and glycemic variability was independent of disease severity, but the effect of hydrocortisone treatment on blood glucose variability was less strong in the more severely ill patients. The association between hydrocortisone and insulin infusion rate variability was also independent of disease severity, and independent of glycemic variability. CONCLUSIONS: Bolus infusion of hydrocortisone is independently associated with higher glycemic variability and higher insulin infusion rate variability in ICU patients. Studies are needed to see if continuous infusion of hydrocortisone prevents higher glycemic variability and higher insulin infusion rate variability.

Health Economic Evaluation of a Strict Glucose Control Guideline Implemented Using Point-of-Care Testing in Three Intensive Care Units in The Netherlands.

BACKGROUND: Point-of-care testing of blood glucose (BG-POCT) is essential for safe and effective insulin titrations in critically ill patients under glucose control with insulin. The costs associated with this practice are considered substantial, especially when more frequent blood glucose (BG) testing is needed, as with more strict glucose control (SGC) aiming for lower BG levels. OBJECTIVE: The objective of this study was to estimate, from a hospital perspective, the incremental cost effectiveness of an SGC guideline, aiming for BG levels of 4.4-6.1 mmol/L, compared to the situation before implementation of that guideline (aiming for BG levels <8.3 mmol/L), both using BG-POCT. METHODS: This is a secondary analysis of a guideline implementation project aiming for implementation of a guideline of SGC in three intensive care units in The Netherlands. A Markov model including the four health states 'target glucose', 'hyperglycaemia' (defined as BG levels >6.1 mmol/L), 'hypoglycaemia' (defined as BG levels <4.4 mmol/L) and 'in-hospital death' was developed to compare expected costs, number of patients within target and number of life-years saved before and after implementation of the SGC guideline. The effectiveness estimates are based on empirical data from 3195 patients 12 and 24 months before and after implementation of the guideline, respectively. All costs have been converted to price year 2013, and are estimated based on hospital data, the literature and available price lists. RESULTS: The number of BG-POCT increased from 4.8 [interquartile range (IQR) 2.6-6.7] to 8.0 [IQR 4.1-11.2] per patient per day, accruing 58% higher costs for BG-POCT (€13.56 vs. €8.57 per patient) in the SGC protocol versus the situation before implementation. When taking total hospital costs and clinical effects into account, implementation of the SGC guideline increased total hospital costs per patient by 1.8%, i.e., €355 (from €20,617 to €20,972) during the inpatient stay, while the number of patients in target glucose levels increased by 1.4% (i.e., from 881 to 895 per 1000 patients). This translates to an incremental cost-effectiveness ratio of €25 per additional patient within the target glucose level. The model outcomes are most sensitive to changes in ICU length of stay. CONCLUSION: The increase in the number of patients and time within target glucose levels is achieved with a small increase in total direct hospital costs.

Point accuracy and reliability of an interstitial continuous glucose-monitoring device in critically ill patients: a prospective study.

INTRODUCTION: There is a need for continuous glucose monitoring in critically ill patients. The objective of this trial was to determine the point accuracy and reliability of a device designed for continuous monitoring of interstitial glucose levels in intensive care unit patients. METHODS: We evaluated point accuracy by comparing device readings with glucose measurements in arterial blood by using blood gas analyzers. Analytical and clinical accuracy was expressed in Bland-Altman plots, glucose prediction errors, and Clarke error grids. We used a linear mixed model to determine which factors affect the point accuracy. In addition, we determined the reliability, including duration of device start-up and calibration, skips in data acquisition, and premature disconnections of sensors. RESULTS: We included 50 patients in whom we used 105 sensors. Five patients from whom we could not collect the predefined minimum number of four consecutive comparative blood draws were excluded from the point accuracy analysis. Therefore, we had 929 comparative samples from 100 sensors in 45 patients (11 (7 to 28) samples per patient) during 4,639 hours (46 (27 to 134) hours per patient and 46 (21 to 69) hours per sensor) for the accuracy analysis. Point accuracy did not meet the International Organization for Standardization (ISO) 14971 standard for insulin dosing accuracy but did improve with increasing numbers of calibrations and was better in patients who did not have a history of diabetes. Out of 105 sensors, 60 were removed prematurely for a variety of reasons. The device start-up time was 49 (43 to 58) minutes. The number of skips in data acquisition was low, resulting in availability of real-time data during 95% (89% to 98%) of the connection time per sensor. CONCLUSIONS: The point accuracy of a device designed for continuous real-time monitoring of interstitial glucose levels was relatively low in critically ill patients. The device had few downtimes, but one third of the sensors were removed prematurely because of unresolved sensor- or device-related problems. TRIAL REGISTRATION: Netherlands Trial Registry number: NTR3827 . Registered 30 January 2013.

Glucose prediction by analysis of exhaled metabolites - a systematic review.

BACKGROUND: In critically ill patients, glucose control with insulin mandates time- and blood-consuming glucose monitoring. Blood glucose level fluctuations are accompanied by metabolomic changes that alter the composition of volatile organic compounds (VOC), which are detectable in exhaled breath. This review systematically summarizes the available data on the ability of changes in VOC composition to predict blood glucose levels and changes in blood glucose levels. METHODS: A systematic search was performed in PubMed. Studies were included when an association between blood glucose levels and VOCs in exhaled air was investigated, using a technique that allows for separation, quantification and identification of individual VOCs. Only studies on humans were included. RESULTS: Nine studies were included out of 1041 identified in the search. Authors of seven studies observed a significant correlation between blood glucose levels and selected VOCs in exhaled air. Authors of two studies did not observe a strong correlation. Blood glucose levels were associated with the following VOCs: ketone bodies (e.g., acetone), VOCs produced by gut flora (e.g., ethanol, methanol, and propane), exogenous compounds (e.g., ethyl benzene, o-xylene, and m/p-xylene) and markers of oxidative stress (e.g., methyl nitrate, 2-pentyl nitrate, and CO). CONCLUSION: There is a relation between blood glucose levels and VOC composition in exhaled air. These results warrant clinical validation of exhaled breath analysis to monitor blood glucose levels.

Interobserver agreement of Centers for Disease Control and Prevention criteria for classifying infections in critically ill patients.

OBJECTIVES: Correct classification of the source of infection is important in observational and interventional studies of sepsis. Centers for Disease Control and Prevention criteria are most commonly used for this purpose, but the robustness of these definitions in critically ill patients is not known. We hypothesized that in a mixed ICU population, the performance of these criteria would be generally reduced and would vary among diagnostic subgroups. DESIGN: Prospective cohort. SETTING: Data were collected as part of a cohort of 1,214 critically ill patients admitted to two hospitals in The Netherlands between January 2011 and June 2011. PATIENTS: Eight observers assessed a random sample of 168 of 554 patients who had experienced at least one infectious episode in the ICU. Each patient was assessed by two randomly selected observers who independently scored the source of infection (by affected organ system or site), the plausibility of infection (rated as none, possible, probable, or definite), and the most likely causative pathogen. Assessments were based on a post hoc review of all available clinical, radiological, and microbiological evidence. The observed diagnostic agreement for source of infection was classified as partial (i.e., matching on organ system or site) or complete (i.e., matching on specific diagnostic terms), for plausibility as partial (2-point scale) or complete (4-point scale), and for causative pathogens as an approximate or exact pathogen match. Interobserver agreement was expressed as a concordant percentage and as a kappa statistic. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 206 infectious episodes were observed. Agreement regarding the source of infection was 89% (183/206) and 69% (142/206) for a partial and complete diagnostic match, respectively. This resulted in a kappa of 0.85 (95% CI, 0.79-0.90). Agreement varied from 63% to 91% within major diagnostic categories and from 35% to 97% within specific diagnostic subgroups, with the lowest concordance observed in cases of ventilator-associated pneumonia. In the 142 episodes for which a complete match on source of infection was obtained, the interobserver agreement for plausibility of infection was 83% and 65% on a 2- and 4-point scale, respectively. For causative pathogen, agreement was 78% and 70% for an approximate and exact pathogen match, respectively. CONCLUSIONS: Interobserver agreement for classifying sources of infection using Centers for Disease Control and Prevention criteria was excellent overall. However, full concordance on all aspects of the diagnosis between independent observers was rare for some types of infection, in particular for ventilator-associated pneumonia.

Diabetic status and the relation of the three domains of glycemic control to mortality in critically ill patients: an international multicenter cohort study.

INTRODUCTION: Hyperglycemia, hypoglycemia, and increased glycemic variability have each been independently associated with increased risk of mortality in critically ill patients. The role of diabetic status on modulating the relation of these three domains of glycemic control with mortality remains uncertain. The purpose of this investigation was to determine how diabetic status affects the relation of hyperglycemia, hypoglycemia, and increased glycemic variability with the risk of mortality in critically ill patients. METHODS: This is a retrospective analysis of prospectively collected data involving 44,964 patients admitted to 23 intensive care units (ICUs) from nine countries, between February 2001 and May 2012. We analyzed mean blood glucose concentration (BG), coefficient of variation (CV), and minimal BG and created multivariable models to analyze their independent association with mortality. Patients were stratified according to the diagnosis of diabetes. RESULTS: Among patients without diabetes, mean BG bands between 80 and 140 mg/dl were independently associated with decreased risk of mortality, and mean BG bands>or=140 mg/dl, with increased risk of mortality. Among patients with diabetes, mean BG from 80 to 110 mg/dl was associated with increased risk of mortality and mean BG from 110 to 180 mg/dl with decreased risk of mortality. An effect of center was noted on the relation between mean BG and mortality. Hypoglycemia, defined as minimum BG<70 mg/dl, was independently associated with increased risk of mortality among patients with and without diabetes and increased glycemic variability, defined as CV>or=20%, was independently associated with increased risk of mortality only among patients without diabetes. Derangements of more than one domain of glycemic control had a cumulative association with mortality, especially for patients without diabetes. CONCLUSIONS: Although hyperglycemia, hypoglycemia, and increased glycemic variability is each independently associated with mortality in critically ill patients, diabetic status modulates these relations in clinically important ways. Our findings suggest that patients with diabetes may benefit from higher glucose target ranges than will those without diabetes. Additionally, hypoglycemia is independently associated with increased risk of mortality regardless of the patient's diabetic status, and increased glycemic variability is independently associated with increased risk of mortality among patients without diabetes.

Glycemic variability is complex--is glucose complexity variable?

Observational studies show an independent association between increased glycemic variability and higher mortality in critically ill patients. Minimization of glycemic variability is therefore suggested as a new target of glycemic control, which may require very frequent or almost continuous monitoring of glucose levels. Brunner and colleagues show the use of real-time subcutaneous continuous glucose monitoring does not decrease glycemic variability. Continuous glucose monitoring, however, may reveal changes in glucose complexity, which may be of interest since both increased and decreased glucose complexity is associated with higher mortality in the critically ill.